Course Coordinator: 
Erik De Schutter
Computational Neuroscience

Explore topics in computational neuroscience, from single neuron properties to networks of integrate-and-fire neurons. Review the biophysical properties of neurons and extend these findings to cable theory and passive dendrite simulations. Study excitability based on the Hodgkin-Huxley model of the action potential and the contributions of various other ion channels. Review phase space analysis, reaction-diffusion modeling and simulating calcium dynamics. Model single neurons, neuronal populations, and networks using NEURON software. Discuss seminal papers associated with each topic, and produce reports on modeling exercises.

This course introduces basic concepts and methods of computational neuroscience based on theory and a sampling of important scientific papers.
Course Content: 
  1. Introduction and the NEURON simulator
  2. Basic concepts and the membrane equation
  3. Linear cable theory
  4. Passive dendrites
  5. Modeling exercises 1
  6. Synapses and passive synaptic integration
  7. Ion channels and the Hodgkin-Huxley model
  8. Neuronal excitability and phase space analysis
  9. Other ion channels
  10. Modeling exercises 2
  11. Reaction-diffusion modeling and calcium dynamics
  12. Nonlinear and adaptive integrate-and-fire neurons
  13. Neuronal populations and network modeling
  14. Synaptic plasticity and learning
Course Type: 
Active participation to textbook discussions in class (40%), reports on modeling papers (40%), written exercises (20%).
Text Book: 
  • Biophysics of Computation, by Christof Koch (1999) Oxford Press
  • Neural Dynamics: From Single Neurons to Networks and Models of Cognition, by Wulram Gerstner, Werner M. Kistler, Richard Naud and Liam Paninski (Cambridge University Press 2014)
Reference Book: 
  • Computational Modeling Methods for Neuroscientists, edited by Erik De Schutter (MIT Press 2010)
Prior Knowledge: 
Requires introductory neuroscience course or equivalent with background knowledge in computational methods, programming, mathematics.